Garbage_classify
本文新增添分类，检测，换脸技术等学习教程，各种调参技巧和tricks，卷积结构详细解析可视化，注意力
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Pythonpark | 8,310 | 4 months ago | Python | |||||||
| Python 开源项目之「自学编程之路」，保姆级教程：AI实验室、宝藏视频、数据结构、学习指南、机器学习实战、深度学习实战、网络爬虫、大厂面经、程序人生、资源分享。 | ||||||||||
| Easypr | 5,583 | 4 years ago | 69 | apache-2.0 | C++ | |||||
| An easy, flexible, and accurate plate recognition project for Chinese licenses in unconstrained situations. | ||||||||||
| Ios_ml | 1,406 | 6 years ago | 2 | |||||||
| List of Machine Learning, AI, NLP solutions for iOS. The most recent version of this article can be found on my blog. | ||||||||||
| Rumale | 723 |  | 19 | 4 months ago | 5 | November 12, 2023 | 1 | bsd-3-clause | Ruby | |
| Rumale is a machine learning library in Ruby | ||||||||||
| Garbage_classify | 418 | 3 years ago | 46 | Python | ||||||
| 本文新增添分类，检测，换脸技术等学习教程，各种调参技巧和tricks，卷积结构详细解析可视化，注意力机制代码等详解！本次垃圾分类挑战杯，目的在于构建基于深度学习技术的图像分类模型，实现垃圾图片类别的精准识别，大赛参考深圳垃圾分类标准，按可回收物、厨余垃圾、有害垃圾和其他垃圾四项分类。本项目包含完整的分类网络、数据增强、SVM等各种分类增强策略，后续还会继续更新新的分类技巧。 | ||||||||||
| Cnn Svm | 151 | 4 years ago | 3 | apache-2.0 | Python | |||||
| An Architecture Combining Convolutional Neural Network (CNN) and Linear Support Vector Machine (SVM) for Image Classification | ||||||||||
| Malware Classification | 140 | a year ago | 3 | gpl-3.0 | Python | |||||
| Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification | ||||||||||
| Compendium Of Free Ml Reading Resources | 106 | 4 months ago | ||||||||
| Compendium of free ML reading resources | ||||||||||
| Sw_machine_learning | 95 | 5 years ago | 1 | Jupyter Notebook | ||||||
| machine learning | ||||||||||
| Gru Svm | 70 | 4 years ago | agpl-3.0 | Python | ||||||
| [ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection | ||||||||||
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